{"title":"Real-time image distortion correction: Analysis and evaluation of FPGA-compatible algorithms","authors":"Paolo Di Febbo, S. Mattoccia, Carlo Dal Mutto","doi":"10.1109/ReConFig.2016.7857182","DOIUrl":null,"url":null,"abstract":"Image distortion correction is a critical preprocessing step for a variety of computer vision and image processing algorithms. Standard real-time software implementations are generally not suited for direct hardware porting, so appropriated versions need to be designed in order to obtain implementations deployable on FPGAs. In this paper, hardware-compatible techniques for image distortion correction are introduced and analyzed in details. The considered solutions are compared in terms of output quality by using a geometrical-error-based approach, with particular emphasis on robustness with respect to increasing lens distortion. The required amount of hardware resources is also estimated for each considered approach.","PeriodicalId":431909,"journal":{"name":"2016 International Conference on ReConFigurable Computing and FPGAs (ReConFig)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on ReConFigurable Computing and FPGAs (ReConFig)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ReConFig.2016.7857182","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Image distortion correction is a critical preprocessing step for a variety of computer vision and image processing algorithms. Standard real-time software implementations are generally not suited for direct hardware porting, so appropriated versions need to be designed in order to obtain implementations deployable on FPGAs. In this paper, hardware-compatible techniques for image distortion correction are introduced and analyzed in details. The considered solutions are compared in terms of output quality by using a geometrical-error-based approach, with particular emphasis on robustness with respect to increasing lens distortion. The required amount of hardware resources is also estimated for each considered approach.